U.S. patent application number 17/169805 was filed with the patent office on 2021-12-02 for glomerulonephritis biomarkers.
This patent application is currently assigned to Meso Scale Technologies, LLC.. The applicant listed for this patent is Meso Scale Technologies, LLC.. Invention is credited to Eli N. Glezer, John Kenten, Galina Nikolenko.
Application Number | 20210373033 17/169805 |
Document ID | / |
Family ID | 1000005770061 |
Filed Date | 2021-12-02 |
United States Patent
Application |
20210373033 |
Kind Code |
A1 |
Glezer; Eli N. ; et
al. |
December 2, 2021 |
GLOMERULONEPHRITIS BIOMARKERS
Abstract
The present invention relates to methods of diagnosing
glomerulonephritis (GN) in a patient, as well as methods of
monitoring the progression of GN and/or methods of monitoring a
treatment protocol of a therapeutic agent or a therapeutic regimen.
The invention also relates to assay methods used in connection with
the diagnostic methods described herein.
Inventors: |
Glezer; Eli N.; (Del Mar,
CA) ; Kenten; John; (Boyds, MD) ; Nikolenko;
Galina; (Germantown, MD) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Meso Scale Technologies, LLC. |
Rockville |
MD |
US |
|
|
Assignee: |
Meso Scale Technologies,
LLC.
Rockville
MD
|
Family ID: |
1000005770061 |
Appl. No.: |
17/169805 |
Filed: |
February 8, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14168688 |
Jan 30, 2014 |
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17169805 |
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61759434 |
Feb 1, 2013 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N 2800/52 20130101;
G01N 33/6893 20130101; G01N 2800/347 20130101 |
International
Class: |
G01N 33/68 20060101
G01N033/68 |
Claims
1. A method of detecting glomerulonephritis (GN) in a patient, said
method comprising (a) obtaining a test sample from the patient; (b)
measuring a level of three or more of a plurality of biomarkers in
said sample, said plurality of biomarkers selected from (a) a first
group consisting of aGST, IL-6, CHGA, E-Cadherin, Timp-1, TNF-RI,
and TNF-RII, and (b) a second group consisting of EGF, UMOD, and
SERPINB3, wherein at least one of said three biomarkers is a
biomarker from the second group and at least one of said three
biomarkers is a biomarker from the first group; (c) comparing said
levels to normal control levels of said biomarkers, wherein (i) an
increase in the concentration of each of the plurality of
biomarkers in the first group, and (ii) a decrease in the
concentration of each of the plurality of biomarkers in the second
group, as compared to the normal control indicates that the patient
has GN; and (d) evaluating from said comparing step (c) whether the
patient has GN.
2. A method of detecting glomerulonephritis (GN), said method
comprising (a) ordering a test comprising a measurement of a level
of three or more of a plurality of biomarkers in a test sample
obtained from a patient, said plurality of biomarkers selected from
(a) a first group consisting of aGST, IL-6, CHGA, E-Cadherin,
Timp-1, TNF-RI, and TNF-RII, and (b) a second group consisting of
EGF, UMOD, and SERPINB3, wherein at least one of said three
biomarkers is a biomarker from the second group and at least one of
said three biomarkers is a biomarker from the first group; (b)
comparing said levels to normal control levels of said biomarkers,
wherein (i) an increase in the concentration of each of the
plurality of biomarkers in the first group, and (ii) a decrease in
the concentration of each of the plurality of biomarkers in the
second group, as compared to the normal control indicates that the
patient has GN; and (c) evaluating from said comparing step (b)
whether the patient has GN.
3. A method of detecting glomerulonephritis (GN), comprising: (a)
obtaining a test sample from a patient; (b) measuring a level of
three or more of a plurality of biomarkers in said sample, said
plurality of biomarkers selected from (a) a first group consisting
of aGST, IL-6, CHGA, E-Cadherin, Timp-1, TNF-RI, and TNF-RII, and
(b) a second group consisting of EGF, UMOD, and SERPINB3, wherein
at least one of said three biomarkers is a biomarker from the
second group and at least one of said three biomarkers is a
biomarker from the first group; (c) comparing said levels to normal
control levels of said biomarkers; (d) evaluating from said
comparing step (c) whether the patient has GN; and (e)
administering a treatment regimen based on said evaluating step
(d).
4. A method of detecting glomerulonephritis (GN), comprising: (a)
obtaining a test sample from a patient prior to the commencement of
a treatment regimen for GN; (b) measuring a level of three or more
of a plurality of biomarkers in said sample, said plurality of
biomarkers selected from (a) a first group consisting of aGST,
IL-6, CHGA, E-Cadherin, Timp-1, TNF-RI, and TNF-RII, and (b) a
second group consisting of EGF, UMOD, and SERPINB3, wherein at
least one of said three biomarkers is a biomarker from the second
group and at least one of said three biomarkers is a biomarker from
the first group; (c) comparing said levels to normal control levels
of said biomarkers; (d) evaluating from said comparing step (c)
whether said patient will be responsive to said treatment regimen;
and (e) administering said treatment regimen based on said
evaluating step (d).
5. A method of detecting glomerulonephritis (GN), comprising: (a)
evaluating a level of three or more of a plurality of biomarkers in
said sample, said plurality of biomarkers selected from (a) a first
group consisting of aGST, IL-6, CHGA, E-Cadherin, Timp-1, TNF-RI,
and TNF-RII, and (b) a second group consisting of EGF, UMOD, and
SERPINB3, wherein at least one of said three biomarkers is a
biomarker from the second group and at least one of said three
biomarkers is a biomarker from the first group; and (b) adjusting a
treatment regimen based on said evaluating step (a).
6. A method of detecting glomerulonephritis (GN), comprising: (a)
evaluating a level of three or more of a plurality of biomarkers in
a test sample obtained from a patient prior to the commencement of
said treatment regimen for GN relative to normal control levels of
said biomarkers, wherein said plurality of biomarkers selected from
(a) a first group consisting of aGST, IL-6, CHGA, E-Cadherin,
Timp-1, TNF-RI, and TNF-RII, and (b) a second group consisting of
EGF, UMOD, and SERPINB3, wherein at least one of said three
biomarkers is a biomarker from the second group and at least one of
said three biomarkers is a biomarker from the first group; and (b)
administering said treatment regimen based on said evaluating step
(a).
7. A method according to claim 1 wherein said measuring step
comprises conducting a multiplexed assay measurement of a plurality
of said biomarkers in said test sample, wherein said multiplexed
assay measurement is conducted using one reaction volume comprising
said test sample.
8. The method of claim 1 wherein said method comprises measuring
levels of four or more biomarkers.
9. The method of claim 8 wherein said measuring step comprises
measuring levels of an additional biomarker comprising Clusterin,
KIM-1, OPGN, Calbindin, Osteoactin, Albumin, B2M, Cystatin C, NGAL,
MCP-1, IL-15, ICAM-1, KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4,
TIMP-1, VCAM-1, and combinations thereof.
10. A method of claim 8 wherein said additional biomarker are
selected from: Clusterin, and KIM 1.
11.-13. (canceled)
14. The method of claim 1 further comprising determining from said
level of said biomarkers the disease progression of GN.
15.-26. (canceled)
27. The method of claim 1, wherein said sample comprises serum and
wherein said measuring step comprises measuring levels of an
additional biomarker comprising Clusterin, KIM 1, and combinations
thereof.
28. The method of claim 1, wherein said sample comprises urine and
wherein said measuring step comprises measuring levels of an
additional biomarker comprising OPGN, Calbindin, Clusterin,
Osteoactin, Albumin, B2M, Cystatin C, NGAL, MCP-1, IL-15, ICAM-1,
KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4, VCAM 1, and combinations
thereof.
29. The method of claim 1 wherein said sample comprises serum
and/or urine and wherein said measuring step comprises measuring
levels of an additional biomarker comprising OPGN, Calbindin,
Clusterin, Osteoactivin, TFF3, B2M, Cystatin C, EGF, NGAL, MCP-1,
IL-6, IL-8, IL-15, IL-7, SERPINB3, CHGA, ICAM-1, KDR, LBP, PRDX4,
Prolactin, PSAT1, S100A4, TIMP-1, TNF-R1, TNF-RII, VCAM-1 and
combinations thereof.
30. The method of claim 29 wherein said method further comprises
determining fractional excretion of said biomarkers.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a divisional of copending U.S. patent
application Ser. No. 14/168,688 filed on Jan. 30, 2014, which
claims the benefit of U.S. Provisional Application No. 61/759,434
filed on Feb. 1, 2013, the entire contents of which are
incorporated herein by reference.
FIELD OF THE INVENTION
[0002] This application relates to assay methods useful in the
detection and treatment of glomerulonephritis.
BACKGROUND OF THE INVENTION
[0003] Glomerulonephritis, also known as glomerular nephritis,
abbreviated GN, is a renal disease (usually of both kidneys)
characterized by inflammation of the glomeruli, or small blood
vessels in the kidneys. GN is a type of renal disease in which the
part of the kidneys that filter waste and fluids from the blood is
damaged. Damage to the glomeruli causes blood and protein to be
lost in the urine. While the exact cause of GN can be difficult to
determine, it can be caused by immunological problems. GN can
develop quickly, and kidney function can be lost within weeks or
months (called rapidly progressive GN). A quarter of people with
chronic GN have no history of kidney disease, but certain
conditions can increase an individual's risk of developing GN,
including but not limited to, blood or lymphatic system disorders,
exposure to hydrocarbon solvents, and a history of cancer,
infections such as strep infections, viruses, heart infections, or
abscesses. Many conditions cause or increase the risk for GN,
including amyloidosis, anti-glomerular basement membrane antibody
disease, blood vessel diseases, such as vasculitis or
polyarteritis, focal segmental glomerulosclerosis, goodpasture
syndrome, heavy use of pain relievers, especially NSAIDs,
Henoch-Schonlein purpura, IgA nephropathy, Lupus nephritis, and
membranoproliferative GN.
SUMMARY OF THE INVENTION
[0004] The invention provides a method for evaluating the efficacy
of a treatment regimen in a patient diagnosed with
glomerulonephritis (GN), said method comprising
[0005] (a) obtaining a test sample from a patient undergoing said
treatment regimen for GN;
[0006] (b) measuring a level of a biomarker in said test sample,
wherein said biomarker comprises Clusterin, KIM-1, aGST, IL-6,
CHGA, E-Cadherin, Timp-1, TNF-RI, TNF-RII, UMOD, OPGN, Calbindin,
Osteoactin, Albumin, B2M, Cystatin C, NGAL, MCP-1, IL-15, ICAM-1,
KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4, TIMP-1, VCAM-1, EGF,
SERPINB3, and combinations thereof;
[0007] (c) comparing said level to a normal control level of said
biomarker; and
[0008] (d) evaluating from said comparing step (c) whether said
patient is responsive to said treatment regimen.
[0009] In one embodiment, the invention includes a method for
evaluating the efficacy of a treatment regimen in a patient
diagnosed with glomerulonephritis (GN), said method comprising
[0010] (a) ordering a test comprising a measurement of a level of a
biomarker in a test sample obtained from a patient undergoing said
treatment regimen for GN, wherein said biomarker comprises
Clusterin, KIM-1, aGST, IL-6, CHGA, E-Cadherin, Timp-1, TNF-RI,
TNF-RII, UMOD, OPGN, Calbindin, Osteoactin, Albumin, B2M, Cystatin
C, NGAL, MCP-1, IL-15, ICAM-1, KDR, LBP, PRDX4, Prolactin, PSAT1,
S100A4, TIMP-1, VCAM-1, EGF, SERPINB3, and combinations
thereof;
[0011] (b) comparing said level to a normal control level of said
biomarker; and
[0012] (c) evaluating from said comparing step (b) whether said
patient is responsive to said treatment regimen.
[0013] Moreover, the invention provides a method of administering a
treatment regimen to a patient in need thereof for treating
glomerulonephritis (GN), comprising:
[0014] (a) obtaining a test sample from a patient undergoing said
treatment regimen for GN;
[0015] (b) measuring a level of a biomarker in said test sample,
wherein said biomarker comprises Clusterin, KIM-1, aGST, IL-6,
CHGA, E-Cadherin, Timp-1, TNF-RI, TNF-RII, UMOD, OPGN, Calbindin,
Osteoactin, Albumin, B2M, Cystatin C, NGAL, MCP-1, IL-15, ICAM-1,
KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4, TIMP-1, VCAM-1, EGF,
SERPINB3, and combinations thereof;
[0016] (c) comparing said level to a normal control level of said
biomarker;
[0017] (d) evaluating from said comparing step (c) whether said
patient is responsive to said treatment regimen; and
[0018] (e) adjusting said treatment regimen based on said
evaluating step (d).
[0019] In addition, the invention contemplates a method of
administering a treatment regimen to a patient in need thereof for
treating glomerulonephritis (GN), comprising:
[0020] (a) obtaining a test sample from a patient prior to the
commencement of said treatment regimen for GN;
[0021] (b) measuring a level of a biomarker in said test sample,
wherein said biomarker comprises Clusterin, KIM-1, aGST, IL-6,
CHGA, E-Cadherin, Timp-1, TNF-RI, TNF-RII, UMOD, OPGN, Calbindin,
Osteoactin, Albumin, B2M, Cystatin C, NGAL, MCP-1, IL-15, ICAM-1,
KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4, TIMP-1, VCAM-1, EGF,
SERPINB3, and combinations thereof;
[0022] (c) comparing said level to a normal control level of said
biomarker;
[0023] (d) evaluating from said comparing step (c) whether said
patient will be responsive to said treatment regimen; and
[0024] (e) administering said treatment regimen based on said
evaluating step (d).
[0025] Still further, the invention includes a method of
administering a treatment regimen to a patient in need thereof for
treating glomerulonephritis (GN), comprising:
[0026] (a) evaluating a level of a biomarker in a test sample
obtained from a patient undergoing said treatment regimen for GN
relative to a normal control level of said biomarker, wherein said
biomarker comprises Clusterin, KIM-1, aGST, IL-6, CHGA, E-Cadherin,
Timp-1, TNF-RI, TNF-RII, UMOD, OPGN, Calbindin, Osteoactin,
Albumin, B2M, Cystatin C, NGAL, MCP-1, IL-15, ICAM-1, KDR, LBP,
PRDX4, Prolactin, PSAT1, S100A4, TIMP-1, VCAM-1, EGF, SERPINB3, and
combinations thereof; and
[0027] (b) adjusting said treatment regimen based on said
evaluating step (a).
[0028] Also provided is a method of administering a treatment
regimen to a patient in need thereof for treating
glomerulonephritis (GN), comprising:
[0029] (a) evaluating a level of a biomarker in a test sample
obtained from a patient prior to the commencement of said treatment
regimen for GN relative to a normal control level of said
biomarker, wherein said biomarker comprises Clusterin, KIM-1, aGST,
IL-6, CHGA, E-Cadherin, Timp-1, TNF-RI, TNF-RII, UMOD, OPGN,
Calbindin, Osteoactin, Albumin, B2M, Cystatin C, NGAL, MCP-1,
IL-15, ICAM-1, KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4, TIMP-1,
VCAM-1, EGF, SERPINB3, and combinations thereof; and
[0030] (b) administering said treatment regimen based on said
evaluating step (a).
[0031] Moreover, the invention provides a multiplexed assay kit
used to evaluate the efficacy of a treatment regimen in a patient
diagnosed with glomerulonephritis (GN), said kit is configured to
measure a level of a plurality of biomarkers in a patient sample,
said plurality of biomarkers comprises Clusterin, KIM-1, aGST,
IL-6, CHGA, E-Cadherin, Timp-1, TNF-RI, TNF-RII, UMOD, and
combinations thereof.
[0032] In one embodiment, a kit is provided for the analysis of a
kidney disease panel comprising
[0033] (a) a multi-well assay plate comprising a plurality of
wells, each well comprising at least four discrete binding domains
to which capture antibodies to the following human analytes are
bound: Clusterin, KIM-1, aGST, IL-6, CHGA, E-Cadherin, Timp-1,
INF-RI, TNF-RII, UMOD, and combinations thereof;
[0034] (b) in one or more vials, containers, or compartments, a set
of labeled detection antibodies specific for said human analytes;
and
[0035] (c) in one or more vials, containers, or compartments, a set
of calibrator proteins.
BRIEF DESCRIPTION OF THE FIGURES
[0036] FIG. 1 shows elected urine biomarkers with elevated median
levels in GN relative to patients with normal kidney function
(N).
[0037] FIG. 2 shows biomarkers with lower median levels in GN
patients relative to patients with normal kidney function (N)
(biomarkers measured in urine samples are designated by the name of
the biomarker followed by the designation "-u", e.g., EGF-u,
UMOD-u, SerpinB3-u and ANXA1-u and serum UMOD-s).
DETAILED DESCRIPTION OF THE INVENTION
[0038] Unless otherwise defined herein, scientific and technical
terms used in connection with the present invention shall have the
meanings that are commonly understood by those of ordinary skill in
the art. Further, unless otherwise required by context, singular
terms shall include pluralities and plural terms shall include the
singular. The articles "a" and "an" are used herein to refer to one
or to more than one (i.e., to at least one) of the grammatical
object of the article. By way of example, "an element" means one
element or more than one element.
[0039] As used herein, the term "sample" is intended to mean any
biological fluid, cell, tissue, organ or combinations or portions
thereof, which includes or potentially includes a biomarker of a
disease of interest. For example, a sample can be a histologic
section of a specimen obtained by biopsy, or cells that are placed
in or adapted to tissue culture. A sample further can be a
subcellular fraction or extract, or a crude or substantially pure
nucleic acid molecule or protein preparation. In one embodiment,
the samples that are analyzed in the assays of the present
invention are blood, peripheral blood mononuclear cells (PBMC),
isolated blood cells, serum and plasma. Other suitable samples
include biopsy tissue, intestinal mucosa, saliva, cerebral spinal
fluid, and urine. In a preferred embodiment, samples used in the
assays of the invention are serum samples.
[0040] A "biomarker" is a substance that is associated with a
particular disease. A change in the levels of a biomarker may
correlate with the risk or progression of a disease or with the
susceptibility of the disease to a given treatment. A biomarker may
be useful in the diagnosis of disease risk or the presence of
disease in an individual, or to tailor treatments for the disease
in an individual (choices of drug treatment or administration
regimes and/or to predict responsiveness or non-responsiveness to a
particular therapeutic regimen). In evaluating potential drug
therapies, a biomarker may be used as a surrogate for a natural
endpoint such as survival or irreversible morbidity. If a treatment
alters a biomarker that has a direct connection to improved health,
the biomarker serves as a "surrogate endpoint" for evaluating
clinical benefit. A sample that is assayed in the diagnostic
methods of the present invention may be obtained from any suitable
patient, including but not limited to a patient suspected of having
GN or a patient having a predisposition to GN. The patient may or
may not exhibit symptoms associated with one or more of these
conditions.
[0041] "Level" refers to the amount, concentration, or activity of
a biomarker. The term "level" may also refer to the rate of change
of the amount, concentration or activity of a biomarker. A level
can be represented, for example, by the amount or synthesis rate of
messenger RNA (mRNA) encoded by a gene, the amount or synthesis
rate of polypeptide corresponding to a given amino acid sequence
encoded by a gene, or the amount or synthesis rate of a biochemical
form of a biomarker accumulated in a cell, including, for example,
the amount of particular post-synthetic modifications of a
biomarker such as a polypeptide, nucleic acid or small molecule.
The term can be used to refer to an absolute amount of a biomarker
in a sample or to a relative amount of the biomarker, including
amount or concentration determined under steady-state or
non-steady-state conditions. Level may also refer to an assay
signal that correlates with the amount, concentration, activity or
rate of change of a biomarker. The level of a biomarker can be
determined relative to a control marker or an additional biomarker
in a sample.
[0042] As shown in Table 1, certain biomarkers were found to be
altered in serum and urine GN patient samples:
TABLE-US-00001 TABLE 1 Sample Change relative to type normal
control Biomarker(s) Serum elevated Clusterin, KIM-1, aGST, IL-6,
CHGA, E-Cadherin, Timp-1, TNF-RI and TNF-RII. decreased UMOD Urine
elevated OPGN, Calbindin, Clusterin, Osteoactin, Albumin, B2M,
Cystatin C, NGAL, MCP-1, IL-6, IL-15, CHGA, E-Cadherin, ICAM-1,
KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4, TIMP-1, TNF-RI, TNF-RII
and VCAM-1 decreased EGF, UMOD, and SERPINB3
[0043] In addition to the serum and urine biomarker levels,
fractional excretion (FE) was assessed as a measure of the rate of
excretion of the biomarker
[FE=U/S[analyte]/U/S[creatinine].times.100%]. Using FE, the
following biomarkers were identified as having altered excretion
rates in GN patients: OPGN, Calbindin, Clusterin, Osteoactivin,
TFF3, B2M, Cystatin C, EGF, NGAL, MCP-1, IL-6, IL-8, IL-15, IL-7,
SERPINB3, CHGA, ICAM-1, KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4,
TIMP-1, TNF-R1, TNF-RII and VCAM-1.
[0044] One or more of the biomarkers listed above can be used for
the diagnosis of GN and/or to assess susceptibility of GN in a
patient to a treatment regimen. For example, these biomarkers can
be used in a diagnostic method, alone or in combination with other
biomarkers for GN and/or diagnostic tests for GN, to diagnose GN in
a patient. Alternatively or additionally, these biomarkers can be
used to monitor a therapeutic regimen used for the treatment of GN
to assess the efficacy of the regimen for a given patient.
[0045] The method of the present invention can include assessing
the efficacy of a therapeutic regimen for GN and/or the
susceptibility of a patient to a therapeutic regimen. In general,
the goal of treatment for GN is to protect the kidneys from further
damage and accordingly, one or more of the biomarkers listed above
can be analyzed in combination with one or more biomarkers
indicative of renal function, including but not limited to
Lipocalin-2, osteopontin, albumin, TIM-1, NGAL, alpha GST,
calbindin, clusterin, KIM-1, osteoactivin, TFF3, VEGF, cystatin C,
EGF, OPN, and UMOD. Controlling a patient's blood pressure is
critical to protecting the kidneys and slow the decline of kidney
function. Accordingly, diuretics, angiotensin-converting enzyme
(ACE) inhibitors, and/or angiotensin II receptor agonists can be
used to protect the kidneys from further damage. If an underlying
cause of GN has been identified, additional therapeutic agents can
be administered, alone or in combination with one or more
anti-hypertensive agents, including but not limited to: antibiotics
(if GN resulted from a bacterial infection), corticosteroids and
immunosuppressants (if GN resulted from Lupus or vasculitis), fish
oil supplements and immunosuppressants (if GN resulted from IgA
nephropathy), and plasmapheresis (if GN resulted from Goodpasture's
syndrome). The biomarkers identified herein can be assessed before,
during and/or after a treatment regimen including one or more such
medications to assess disease progression.
[0046] Moreover, a therapeutic regimen may include administration
of a therapeutic agent or a combination of therapeutic agents to a
patient one or more times over a given time period. This treatment
regimen may be accompanied by the administration of one or more
additional therapeutic or palliative agents. The level(s) of
biomarkers may be measured before treatment, one or more times
during the administration period, and/or after treatment is
suspended. Therefore, the method may include measuring an interim
level of a biomarker during the therapeutic regimen and the method
includes evaluating biomarker levels by comparing that level, the
interim level and the baseline level. In addition, the level of a
biomarker may be determined at any time point before and/or after
initiation of treatment. In one embodiment, the biomarker is used
to gauge the efficacy of a therapeutic regimen. Therefore, the
method of the present invention may include measuring a baseline
level(s) of a biomarker before a therapeutic regimen is initiated,
and the method includes evaluating biomarker levels by comparing
the level and the baseline level.
[0047] Still further, the method can include measuring a level(s)
of a biomarker before a therapeutic regimen is initiated to predict
whether GN will be responsive or non-responsive to a given
therapeutic regimen. The method may further comprise modifying the
therapeutic regimen based on the level(s) of a biomarker observed
during this preliminary and/or interim measuring step, e.g.,
increasing or decreasing the dosage, frequency, or route of
administration of a therapeutic agent, adding an additional
therapeutic agent and/or palliative agent to a treatment regimen,
or if the therapeutic regimen includes the administration of two or
more therapeutic and/or palliative agents, the treatment regimen
may be modified to eliminate one or more of the therapeutic and/or
palliative agents used in the combination therapy.
[0048] Still further, the method can include comparing the level of
a biomarker to a detection cut-off level, wherein a level above the
detection cut-off level is indicative of GN. Alternatively, the
evaluating step comprises comparing a level of a biomarker to a
detection cut-off level, wherein a level below the detection
cut-off level is indicative of GN. In one embodiment of the present
invention, the level of a biomarker is compared to a detection
cut-off level or range, wherein the biomarker level above or below
the detection cut-off level (or within the detection cut-off range)
is indicative of GN. Furthermore, the levels of two or more
biomarkers may both be used to make a determination. For example,
i) having a level of at least one of the markers above or below a
detection cut-off level (or within a detection cut-off range) for
that marker is indicative of GN; ii) having the level of two or
more (or all) of the markers above or below a detection cut-off
level (or within a detection cut-off range) for each of the markers
is indicative of GN; or iii) an algorithm based on the levels of
the multiple markers is used to determine if GN is present.
[0049] The methods of the invention can be used alone or in
combination with other diagnostic tests or methods to diagnose a
patient with GN. The following tests/criteria are generally used by
clinicians to diagnose a patient with GN, and this set of tests can
be considered in combination with a diagnostic screen for the
biomarkers identified herein to diagnose a patient with GN: [0050]
Clinical symptoms: anemia, high blood pressure, reduced kidney
function, signs of chronic kidney disease may be seen, including:
nerve inflammation (polyneuropathy), signs of fluid overload,
including abnormal heart and lung sounds, edema; [0051] Imaging
tests: abdominal CT scan, kidney ultrasound, chest x-ray,
intravenous pyelogram (IVP) [0052] Urinalysis and other urine tests
include: creatinine clearance, urine fortotal protein, uric acid in
the urine; urine concentration test, urine creatinine, urine
protein, urine RBC, urine specific gravity, urine osmolality [0053]
Blood tests: albumin, anti-glomerular basement membrane antibody
test, anti-neutrophil cytoplasmic antibodies (ANCAs), anti-nuclear
antibodies, BUN and creatinine.
[0054] As described herein, the measured levels of one or more
biomarkers may be used to detect or monitor GN and/or to determine
the responsiveness of GN to a specific treatment regimen. The
specific methods/algorithms for using biomarker levels to make
these determinations, as described herein, may optionally be
implemented by software running on a computer that accepts the
biomarker levels as input and returns a report with the
determinations to the user. This software may run on a standalone
computer or it may be integrated into the software/computing system
of the analytical device used to measure the biomarker levels or,
alternatively, into a laboratory information management system
(LIMS) into which crude or processed analytical data is entered. In
one embodiment, biomarkers are measured in a point-of-care clinical
device which carries out the appropriate methods/algorithms for
detecting, monitoring or determining the responsiveness of a
disease and which reports such determination(s) back to the
user.
[0055] According to one aspect of the invention, the level(s) of
biomarker(s) are measured in samples collected from individuals
clinically diagnosed with, suspected of having or at risk of
developing GN. Initial diagnosis may be carried out using
conventional methods. The level(s) of biomarker(s) are also
measured in healthy individuals. Specific biomarkers valuable in
distinguishing between normal and diseased patients are identified
by visual inspection of the data, for example, by visual
classification of data plotted on a one-dimensional or
multidimensional graph, or by using statistical methods such as
characterizing the statistically weighted difference between
control individuals and diseased patients and/or by using Receiver
Operating Characteristic (ROC) curve analysis. A variety of
suitable methods for identifying useful biomarkers and setting
detection thresholds/algorithms are known in the art and will be
apparent to the skilled artisan.
[0056] For example and without limitation, diagnostically valuable
biomarkers may be first identified using a statistically weighted
difference between control individuals and diseased patients,
calculated as
D - N .sigma. D * .sigma. N ##EQU00001##
wherein D is the median level of a biomarker in patients diagnosed
as having, for example, GN, N is the median (or average) of the
control individuals, .sigma..sub.D is the standard deviation of D
and .sigma..sub.N is the standard deviation of N. The larger the
magnitude, the greater the statistical difference between the
diseased and normal populations.
[0057] According to one embodiment of the invention, biomarkers
resulting in a statistically weighted difference between control
individuals and diseased patients of greater than, e.g., 1, 1.5, 2,
2.5 or 3 could be identified as diagnostically valuable
markers.
[0058] Another method of statistical analysis for identifying
biomarkers is the use of z-scores, e.g., as described in Skates et
al. (2007) Cancer Epidemiol. Biomarkers Prey. 16(2):334-341.
[0059] Another method of statistical analysis that can be useful in
the inventive methods of the invention for determining the efficacy
of particular candidate analytes, such as particular biomarkers,
for acting as diagnostic marker(s) is ROC curve analysis. An ROC
curve is a graphical approach to looking at the effect of a cut-off
criterion, e.g., a cut-off value for a diagnostic indicator such as
an assay signal or the level of an analyte in a sample, on the
ability of a diagnostic to correctly identify positive or negative
samples or subjects. One axis of the ROC curve is the true positive
rate (TPR, i.e., the probability that a true positive
sample/subject will be correctly identified as positive, or
alternatively, the false negative rate (FNR=1-TPR, the probability
that a true positive sample/subject will be incorrectly identified
as a negative). The other axis is the true negative rate, i.e.,
TNR, the probability that a true negative sample will be correctly
identified as a negative, or alternatively, the false positive rate
(FPR=1-TNR, the probability that a true negative sample will be
incorrectly identified as positive). The ROC curve is generated
using assay results for a population of samples/subjects by varying
the diagnostic cut-off value used to identify samples/subjects as
positive or negative and plotting calculated values of TPR or FNR
and TNR or FPR for each cut-off value. The area under the ROC curve
(referred to herein as the AUC) is one indication of the ability of
the diagnostic to separate positive and negative samples/subjects.
In one embodiment, a biomarker provides an AUC--0.7. In another
embodiment, a biomarker provides an AUC.gtoreq.0.8. In another
embodiment, a biomarker provides an AUC.gtoreq.0.9.
[0060] Diagnostic indicators analyzed by ROC curve analysis may be
a level of an analyte, e.g., a biomarker, or an assay signal.
Alternatively, the diagnostic indicator may be a function of
multiple measured values, for example, a function of the
level/assay signal of a plurality of analytes, e.g., a plurality of
biomarkers, or a function that combines the level or assay signal
of one or more analytes with a patient's scoring value that is
determined based on visual, radiological and/or histological
evaluation of a patient. The multi-parameter analysis may provide
more accurate diagnosis relative to analysis of a single
marker.
[0061] Candidates for a multi-analyte panel could be selected by
using criteria such as individual analyte ROC areas, median
difference between groups normalized by geometric interquartile
range (IQR) etc. The objective is to partition the analyte space to
improve separation between groups (for example, normal and disease
populations) or to minimize the misclassification rate.
[0062] One approach is to define a panel response as a weighted
combination of individual analytes and then compute an objective
function like ROC area, product of sensitivity and specificity,
etc. See e.g., WO 2004/058055, as well as US2006/0205012, the
disclosures of which are incorporated herein by reference in their
entireties.
[0063] The assays of the present invention may be conducted by any
suitable method. In one embodiment, biomarker levels are measured
in a single sample, and those measurement may be conducted in a
single assay chamber or assay device, including but not limited to
a single well of an assay plate, a single assay cartridge, a single
lateral flow device, a single assay tube, etc. Biomarker levels may
be measured using any of a number of techniques available to the
person of ordinary skill in the art, e.g., direct physical
measurements (e.g., mass spectrometry) or binding assays (e.g.,
immunoassays, agglutination assays and immunochromatographic
assays). The method may also comprise measuring a signal that
results from a chemical reactions, e.g., a change in optical
absorbance, a change in fluorescence, the generation of
chemiluminescence or electrochemiluminescence, a change in
reflectivity, refractive index or light scattering, the
accumulation or release of detectable labels from the surface, the
oxidation or reduction or redox species, an electrical current or
potential, changes in magnetic fields, etc. Suitable detection
techniques may detect binding events by measuring the participation
of labeled binding reagents through the measurement of the labels
via their photoluminescence (e.g., via measurement of fluorescence,
time-resolved fluorescence, evanescent wave fluorescence,
up-converting phosphors, multi-photon fluorescence, etc.),
chemiluminescence, electrochemiluminescence, light scattering,
optical absorbance, radioactivity, magnetic fields, enzymatic
activity (e.g., by measuring enzyme activity through enzymatic
reactions that cause changes in optical absorbance or fluorescence
or cause the emission of chemiluminescence). Alternatively,
detection techniques may be used that do not require the use of
labels, e.g., techniques based on measuring mass (e.g., surface
acoustic wave measurements), refractive index (e.g., surface
plasmon resonance measurements), or the inherent luminescence of an
analyte.
[0064] Binding assays for measuring biomarker levels may use solid
phase or homogenous formats. Suitable assay methods include
sandwich or competitive binding assays. Examples of sandwich
immunoassays are described in U.S. Pat. Nos. 4,168,146 and
4,366,241, both of which are incorporated herein by reference in
their entireties. Examples of competitive immunoassays include
those disclosed in U.S. Pat. Nos. 4,235,601, 4,442,204 and
5,208,535, each of which are incorporated herein by reference in
their entireties.
[0065] Multiple biomarkers may be measured using a multiplexed
assay format, e.g., multiplexing through the use of binding reagent
arrays, multiplexing using spectral discrimination of labels,
multiplexing of flow cytometric analysis of binding assays carried
out on particles, e.g., using the Luminex.RTM. system. Suitable
multiplexing methods include array based binding assays using
patterned arrays of immobilized antibodies directed against the
biomarkers of interest. Various approaches for conducting
multiplexed assays have been described (See e.g., US 20040022677;
US 20050052646; US 20030207290; US 20030113713; US 20050142033; and
US 20040189311, each of which is incorporated herein by reference
in their entireties. One approach to multiplexing binding assays
involves the use of patterned arrays of binding reagents, e.g.,
U.S. Pat. Nos. 5,807,522 and 6,110,426; Delehanty J-B., Printing
functional protein microarrays using piezoelectric capillaries,
Methods Mol. Bio. (2004) 278: 135-44; Lue R Yet al. Site-specific
immobilization of biotinylated proteins for protein microarray
analysis, Methods Mol. Biol. (2004) 278: 85-100; Lovett,
Toxicogenomics: Toxicologists Brace for Genomics Revolution,
Science (2000) 289: 536-537; Berns A, Cancer: Gene expression in
diagnosis, nature (2000),403,491-92; Walt, Molecular Biology:
Bead-based Fiber-Optic Arrays, Science (2000) 287: 451-52 for more
details). Another approach involves the use of binding reagents
coated on beads that can be individually identified and
interrogated. See e.g., WO 9926067, which describes the use of
magnetic particles that vary in size to assay multiple analytes;
particles belonging to different distinct size ranges are used to
assay different analytes. The particles are designed to be
distinguished and individually interrogated by flow cytometry.
Vignali has described a multiplex binding assay in which 64
different bead sets of microparticles are employed, each having a
uniform and distinct proportion of two dyes (Vignali, D. A A,
"Multiplexed Particle-Based Flow Cytometric Assays" J. ImmunoL
Meth. (2000) 243: 243-55). A similar approach involving a set of 15
different beads of differing size and fluorescence has been
disclosed as useful for simultaneous typing of multiple
pneumococcal serotypes (Park, M. K et al., "A Latex Bead-Based Flow
Cytometric Immunoassay Capable of Simultaneous Typing of Multiple
Pneumococcal Serotypes (Multibead Assay)" Clin. Diag. Lab ImmunoL
(2000) 7: 4869). Bishop, J E et al. have described a multiplex
sandwich assay for simultaneous quantification of six human
cytokines (Bishop, LE. et al., "Simultaneous Quantification of Six
Human Cytokines in a Single Sample Using Microparticle-based Flow
Cytometric Technology," Clin. Chem (1999) 45:1693-1694).
[0066] A diagnostic test may be conducted in a single assay
chamber, such as a single well of an assay plate or an assay
chamber that is an assay chamber of a cartridge. The assay modules,
e.g., assay plates or cartridges or multi-well assay plates),
methods and apparatuses for conducting assay measurements suitable
for the present invention are described for example, in US
20040022677; US 20050052646; US 20050142033; US 20040189311, each
of which is incorporated herein by reference in their entireties.
Assay plates and plate readers are commercially available
(MULTI-SPOT.RTM. and MULTI-ARRAY.RTM. plates and SECTOR.RTM.
instruments, Meso Scale Discovery, a division of Meso Scale
Diagnostics, LLC, Rockville, Md.).
[0067] The present invention relates to a kit for the analysis of a
panel of target analytes. The kit is preferably configured to
conduct a multiplexed assay of two or more of the following
analytes: Clusterin, KIM-1, aGST, IL-6, CHGA, E-Cadherin, Timp-1,
TNF-RI, TNF-RII, UMOD, OPGN, Calbindin, Osteoactin, Albumin, B2M,
Cystatin C, NGAL, MCP-1, IL-15, ICAM-1, KDR, LBP, PRDX4, Prolactin,
PSAT1, S100A4, TIMP-1, VCAM-1, EGF, and SERPINB3, and combinations
thereof. The kit can include (a) a single panel arrayed on a
multi-well plate which is configured to be used in an
electrochemiluminescence assay, as well as (b) associated
consumables, e.g., detection antibodies, calibrators, and optional
diluents and/or buffers. Alternatively, the multi-well plates and
associated consumables can be provided separately.
[0068] The panel is preferably configured in a multi-well assay
plate including a plurality of wells, each well having an array
with "spots" or discrete binding domains. Preferably, the array
includes one, four, seven, ten, sixteen, or twenty-five binding
domains, and most preferably, the array includes one, four, seven,
or ten binding domains. A capture antibody to each analyte is
immobilized on a binding domain in the well and that capture
antibody is used to detect the presence of the target analyte in an
immunoassay. Briefly, a sample suspected of containing that analyte
is added to the well and if present, the analyte binds to the
capture antibody at the designated binding domain. The presence of
bound analyte on the binding domain is detected by adding labeled
detection antibody. The detection antibody also binds to the
analyte forming a "sandwich" complex (capture
antibody-analyte-detection antibody) on the binding domain.
[0069] The multiplexed immunoassay kits described herein allow a
user to simultaneously quantify multiple biomarkers. The panels are
selected and optimized such that the individual assays function
well together. The sample may require dilution prior to being
assayed. Sample dilutions for specific sample matrices of interest
are optimized for a given panel to minimize sample matrix effects
and to maximize the likelihood that all the analytes in the panel
will be within the dynamic range of the assay. In a preferred
embodiment, all of the analytes in the panel are analyzed with the
same sample dilution in at least one sample type. In another
preferred embodiment, all of the analytes in a panel are measured
using the same dilution for most sample types.
[0070] For a given panel, the detection antibody concentration and
the number of labels per protein (L/P ratio) for the detection
antibody are adjusted to bring the expected levels of all analytes
into a quantifiable range at the same sample dilution. If one wants
to increase the high end of the quantifiable range for a given
analyte, then the L/P can be decreased and/or the detection
antibody concentration is decreased. On the other hand, if one
wants to increase the lower end of the quantifiable range, the L/P
can be increased, the detection antibody concentration can be
increased if it is not at the saturation level, and/or the
background signal can be lowered.
[0071] Calibration standards for use with the assay panels are
selected to provide the appropriate quantifiable range with the
recommended sample dilution for the panel. The calibration
standards have known concentrations of one of more of the analytes
in the panel. Concentrations of the analytes in unknown samples are
determined by comparison to these standards. In one embodiment,
calibration standards comprise mixtures of the different analytes
measured by an assay panel. Preferably, the analyte levels in a
combined calibrator are selected such that the assay signals for
each analyte are comparable, e.g., within a factor of two, a factor
of five or a factor of 10. In another embodiment, calibration
standards include mixtures of analytes from multiple different
assay panels.
[0072] A calibration curve may be fit to the assay signals measured
with calibration standards using, e.g., curve fits known in the art
such as linear fits, 4-parameter logistic (4-PL) and 5-parameter
(5-PL) fits. Using such fits, the concentration of analytes in an
unknown sample may be determined by backfitting the measured assay
signals to the calculated fits. Measurements with calibration
standards may also be used to determine assay characteristics such
as the limit of detection (LOD), limit of quantification (LOQ),
dynamic range, and limit of linearity (LOL).
[0073] A kit can include the following assay components: a
multi-well assay plate configured to conduct an immunoassay for one
of the panels described herein, a set of detection antibodies for
the analytes in the panel (wherein the set comprises individual
detection antibodies and/or a composition comprising a blend of one
or more individual detection antibodies), and a set of calibrators
for the analytes in the panel (wherein the set comprises individual
calibrator protein compositions and/or a composition comprising a
blend of one or more individual calibrator proteins). The kit can
also include one of more of the following additional components: a
blocking buffer (used to block assay plates prior to addition of
sample), an antibody diluent (used to dilute stock detection
antibody concentrations to the working concentration), an assay
diluent (used to dilute samples), a calibrator diluent (used to
dilute or reconstitute calibration standards) and a read buffer
(used to provide the appropriate environment for detection of assay
labels, e.g., by an ECL measurement). The antibody and assay
diluents are selected to reduce background, optimize specific
signal, and reduce assay interference and matrix effect. The
calibrator diluent is optimized to yield the longest shelf life and
retention of calibrator activity. The blocking buffer should be
optimized to reduce background. The read buffer is selected to
yield the appropriate sensitivity, quantifiable range, and slowest
off-rate.
[0074] The reagent components of the kit can be provided as liquid
reagents, lyophilized, or combinations thereof, diluted or
undiluted, and the kit includes instructions for appropriate
preparation of reagents prior to use. In a preferred embodiment, a
set of detection antibodies are included in the kit comprising a
plurality of individual detection antibody compositions in liquid
form. Moreover, the set of calibrators provided in the kit
preferably comprise a lyophilized blend of calibrator proteins.
Still further, the kit includes a multi-well assay plate that has
been pre-coated with capture antibodies and exposed to a
stabilizing treatment to ensure the integrity and stability of the
immobilized antibodies.
[0075] As part of a multiplexed panel development, assays are
optimized to reduce calibrator and detection antibody non-specific
binding. In sandwich immunoassays, specificity mainly comes from
capture antibody binding. Some considerations for evaluating
multiplexed panels include: (a) detection antibody non-specific
binding to capture antibodies is reduced to lower background of
assays in the panel, and this can be achieved by adjusting the
concentrations and L/P of the detection antibodies; (b)
non-specific binding of detection antibodies to other calibrators
in the panel is also undesirable and should be minimized; (c)
non-specific binding of other calibrators in the panel and other
related analytes should be minimized; if there is calibrator
non-specific binding, it can reduce the overall specificity of the
assays in the panel and it can also yield unreliable results as
there will be calibrator competition to bind the capture
antibody.
[0076] Different assays in the panel may require different
incubation times and sample handling requirements for optimal
performance. Therefore, the goal is to select a protocol that's
optimized for most assays in the panel. Optimization of the assay
protocol includes, but is not limited to, adjusting one or more of
the following protocol parameters: timing (incubation time of each
step), preparation procedure (calibrators, samples, controls,
etc.), and number of wash steps.
[0077] The reagents used in the kits, e.g., the detection and
capture antibodies and calibrator proteins, are preferably
subjected to analytical testing and meet or exceed the
specifications for those tests. The analytical tests that can be
used to characterize kit materials include but are not limited to,
CIEF, DLS, reducing and/or non-reducing EXPERION, denaturing
SDS-PAGE, non-denaturing SDS-PAGE, SEC-MALS, and combinations
thereof. In a preferred embodiment, the materials are characterized
by CIEF, DLS, and reducing and non-reducing EXPERION. One or more
additional tests, including but not limited to denaturing SDS-PAGE,
non-denaturing SDS-PAGE, SEC-MALS, and combinations thereof, can
also be used to characterize the materials. In a preferred
embodiment, the materials are also subjected to functional testing,
i.e., a binding assay for the target analyte, as well as one or
more characterization tests, such as those listed above. If the
materials do not meet or exceed the specifications for the
functional and/or characterization tests, they can be subjected to
additional purification steps and re-tested. Each of these tests
and the metrics applied to the analysis of raw materials subjected
to these tests are described below:
[0078] Capillary Isoelectric Focusing (CIEF) is a technique
commonly used to separate peptides and proteins, and it is useful
in the detection of aggregates. During a CIEF separation, a
capillary is filled with the sample in solution and when voltage is
applied, the ions migrate to a region where they become neutral
(pH=pI). The anodic end of the capillary sits in acidic solution
(low pH), while the cathodic end sits in basic solution (high pH).
Compounds of equal isoelectric points (pI) are "focused" into sharp
segments and remain in their specific zone, which allows for their
distinct detection based on molecular charge and isoelectric point.
Each specific antibody solution will have a fingerprint CIEF that
can change over time. When a protein solution deteriorates, the
nature of the protein and the charge distribution can change.
Therefore, CIEF is a particularly useful tool to assess the
relative purity of a protein solution and it is a preferred method
of characterizing the antibodies and calibrators in the plates and
kits described herein. The metrics used in CIEF include pl of the
main peak, the pl range of the solution, and the profile shape, and
each of these measurements are compared to that of a reference
standard.
[0079] Dynamic Light Scattering (DLS) is used to probe the
diffusion of particulate materials either in solution or in
suspension. By determining the rate of diffusion (the diffusion
coefficient), information regarding the size of particles, the
conformation of macromolecular chains, various interactions among
the constituents in the solution or suspension, and even the
kinetics of the scatterers can be obtained without the need for
calibration. In a DLS experiment, the fluctuations (temporal
variation, typically in a .mu.s to ms time scale) of the scattered
light from scatterers in a medium are recorded and analyzed in
correlation delay time domain. Like CIEF, each protein solution
will generate a fingerprint DLS for the particle size and it's
ideally suited to detect aggregation. All IgGs, regardless of
binding specificity, will exhibit the same DLS particle size. The
metrics used to analyze a protein solution using DLS include
percentage polydispersity, percentage intensity, percentage mass,
and the radius of the protein peak. In a preferred embodiment, an
antibody solution meets or exceeds one or more of the following DLS
specifications: (a) radius of the antibody peak: 4-8 nm (antibody
molecule size); (b) polydispersity of the antibody peak: <40%
(measure of size heterogeneity of antibody molecules); (c)
intensity of the antibody peak: >50% (if other peaks are
present, then the antibody peak is the predominant peak); and (d)
mass in the antibody peak: >50%.
[0080] Reducing and non-reducing gel electrophoresis are techniques
well known in the art. The EXPERION.TM. (Bio-Rad Laboratories,
Inc., www.bio-rad.com) automated electrophoresis station performs
all of the steps of gel-based electrophoresis in one unit by
automating and combining electrophoresis, staining, destaining,
band detection, and imaging into a single step. It can be used to
measure purity. Preferably, an antibody preparation is greater 50%
pure by Experion, more preferably, greater than 75% pure, and most
preferably greater than 80% pure. Metrics that are applied to
protein analysis using non-reducing Experion include percentage
total mass of protein, and for reducing Experion they include
percentage total mass of the heavy and light chains in an antibody
solution, and the heavy to light chain ratio.
[0081] Multi-Angle Light Scattering (MALS) detection can be used in
the stand-alone (batch) mode to measure specific or non-specific
protein interactions, as well as in conjunction with a separation
system such as flow field flow fractionation (FFF) or size
exclusion chromatography (SEC). The combined SEC-MALS method has
many applications, such as the confirmation of the oligomeric state
of a protein, quantification of protein aggregation, and
determination of protein conjugate stoichiometry. Preferably, this
method is used to detect molecular weight of the components of a
sample.
[0082] As used herein, a lot of kits comprise a group of kits
comprising kit components that meet a set of kit release
specifications. A lot can include at least 10, at least 100, at
least 500, at least 1,000, at least 5,000, or at least 10,000 kits
and a subset of kits from that lot are subjected to analytical
testing to ensure that the lot meets or exceeds the release
specifications. In one embodiment, the release specifications
include but are not limited to kit processing, reagent stability,
and kit component storage condition specifications. Kit processing
specifications include the maximum total sample incubation time and
the maximum total time to complete an assay using the kit. Reagent
stability specifications include the minimum stability of each
reagent component of the kit at a specified storage temperature.
Kit storage condition specifications include the range of storage
temperatures for all components of the kit, the maximum storage
temperature for frozen components of the kit, and the maximum
storage temperature for non-frozen components of the kit. A subset
of kits in a lot is reviewed in relation to these specifications
and the size of the subset depends on the lot size. In a preferred
embodiment, for a lot of up to 300 kits, a sampling of 4-7 kits are
tested; for a lot of 300-950 kits, a sampling of 8-10 kits are
tested; and for a lot of greater than 950 kits, a sampling of 10-12
kits are tested. Alternatively or additionally, a sampling of up to
1-5% preferably up to 1-3%, and most preferably up to 2% is
tested.
[0083] In addition, each lot of multi-well assay plates is
preferably subjected to uniformity and functional testing. A subset
of plates in a lot is subjected to these testing methods and the
size of the subset depends on the lot size. In a preferred
embodiment, for a lot of up to 300 plates, a sampling of 4-7 plates
are tested; for a lot of 300-950 plates, a sampling of 8-10 plates
are tested; and for a lot of greater than 950 plates, a sampling of
10-12 plates are tested. Alternatively or additionally, a sampling
of up to 1-5% preferably up to 1-3%, and most preferably up to 2%
is tested. The uniformity and functional testing specifications are
expressed in terms of %CV, Coefficient of Variability, which is a
dimensionless number defined as the standard deviation of a set of
measurements, in this case, the relative signal detected from
binding domains across a plate, divided by the mean of the set.
[0084] One type of uniformity testing is protein A/G testing.
Protein A/G binding is used to confirm that all binding domains
within a plate are coupled to capture antibody. Protein A/G is a
recombinant fusion protein that combines IgG binding domains of
Protein A and protein G and it binds to all subclasses of human
IgG, as well as IgA, IgE, IgM and, to a lesser extent, IgD. Protein
A/G also binds to all subclasses of mouse IgG but not mouse IgA,
IgM, or serum albumin, making it particularly well suited to detect
mouse monoclonal IgG antibodies without interference from IgA, IgM,
and serum albumin that might be present in the sample matrix.
Protein A/G can be labeled with a detectable moiety, e.g., a
fluorescent, chemiluminescent, or electrochemiluminescent label,
preferably an ECL label, to facilitate detection. Therefore, if
capture antibody is adhered to a binding domain of a well, it will
bind to labeled protein A/G, and the relative amount of capture
antibody bound to the surface across a plate can be measured.
[0085] In addition to the uniformity testing described above, a
uniformity metric for a subset of plates within a lot can be
calculated to assess within-plate trending. A uniformity metric is
calculated using a matrix of normalized signals from protein A/G
and/or other uniformity or functional tests. The raw signal data is
smoothed by techniques known in the art, thereby subtracting noise
from the raw data, and the uniformity metric is calculated by
subtracting the minimum signal in the adjusted data set from the
maximum signal.
[0086] In a preferred embodiment, a subset of plates in a lot is
subjected to protein A/G and functional testing and that subset
meet or exceed the following specifications:
TABLE-US-00002 TABLE 2 Plate Metrics Preferred Specification for a
subset Metric of 96 well multi-well plates Average intraplate CV
.ltoreq.10% Maximum intraplate CV .ltoreq.13% Average Uniformity
.ltoreq.25% Maximum Uniformity .ltoreq.37% CV of intraplate
averages .ltoreq.18% Signal, lower boundary >1500 Signal, upper
boundary .sup. <10.sup.(6)
[0087] As disclosed in U.S. Pat. No. 7,842,246 to Wohlstadter et
al., the disclosure of which is incorporated herein by reference in
its entirety, each plate consists of several elements, e.g., a
plate top, a plate bottom, wells, working electrodes, counter
electrodes, reference electrodes, dielectric materials, electrical
connects, and assay reagents. The wells of the plate are defined by
holes/openings in the plate top. The plate bottom can be affixed,
manually or by automated means, to the plate top, and the plate
bottom can serve as the bottom of the well. Plates may have any
number of wells of any size or shape, arranged in any pattern or
configuration, and they can be composed of a variety of different
materials. Preferred embodiments of the invention use industry
standard formats for the number, size, shape, and configuration of
the plate and wells. Examples of standard formats include 96, 384,
1536, and 9600 well plates, with the wells configured in
two-dimensional arrays. Other formats may include single well
plates (preferably having a plurality of assay domains that form
spot patterns within each well), 2 well plates, 6 well plates, 24
well plates, and 6144 well plates. Each well of the plate includes
a spot pattern of varying density, ranging from one spot within a
well to 2, 4, 7, 9, 10, 16, 25, etc., as described hereinabove.
[0088] Each plate is assembled according to a set of preferred
specifications. In a preferred embodiment, a plate bottom meets or
exceeds the following specifications:
TABLE-US-00003 TABLE 3 Plate bottom specifications 96-well (round
well) Parameter specifications in inches Length range (C to C)*
3.8904-3.9004 (A1-A12 and H1-H12) Width range (C to C)
2.4736-2.4836 (A1-A12 and H1-H12) Well to well spacing
0.3513-0.3573 *C to C well distance is the center of spot to center
of spot distance between the outermost wells of a plate.
[0089] In a further preferred embodiment, the plate also meets or
exceeds defined specifications for alignment of a spot pattern
within a well of the plate. These specifications include three
parameters: (a) .DELTA.x, the difference between the center of the
spot pattern and the center of the well along the x axis of the
plate (column-wise, long axis); (b) .DELTA.y, the difference
between the center of the spot pattern and the center of the well
along the y axis of the plate (row-wise, short axis); and (c)
.alpha., the counter-clockwise angle between the long axis of the
plate bottom and the long axis of the plate top of a 96-well plate.
In a preferred embodiment, the plate meets or exceeds the following
specifications: .DELTA.x.ltoreq.0.2 mm, .DELTA.y.ltoreq.0.2 mm, and
.alpha..ltoreq.0.1.degree..
[0090] The following non-limiting examples serve to illustrate
rather than limit the present invention.
EXAMPLES
Measurement of Biomarkers Indicative of Glomerulonephritis
[0091] Urine and serum samples were collected from 23 patients
previously diagnosed with GN and 6 normal control subjects
(patients having normal kidney function). Samples were analyzed in
an immunoassay format and the samples were screened for the
presence/absence of the following set of biomarkers: AKR1 B1,
AKR1C2, Albumin, ALP, ANXA1, B2M, BCL2L2, Calbindin, CHGA,
Clusterin, CRYAB, Cystatin C, E-Cadherin, EGF, EOTAXIN, EOTAXIN-3,
FABP5, GCLM, GLO1, GM-CSF, GPI, GSTM1, GSTM2, ICAM-1, IFN-gamma,
IFN-gamma, IL-10, IL-12P70, IL-13, IL-15, IL-16, IL18, IL-1alpha,
IL-1beta, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IP-10, KDR, KIM-1,
LBP, MAGEA4, MAPK14, MBD1, MCP-1, MCP-4, MDC, MIP-1B, NGAL, NME2,
OCL, ODC1, ONN, OPGN, OPN, osteoactivin, Osteopontin, P-Cadherin,
PPP2R4, PRDX4, Prolactin, PSAT1, RAC1, RANTES, S100A4, S100A6,
SAT1, SERPINB3, SFN, SOST, TARC, TFF3, TIMP-1, TNF RI, TNF RII,
TNF-alpha, UMOD, VCAM-1, VEGF and .alpha.GST.
[0092] In general, the assay format was as follows, (all
consumables, reagents, and instruments referenced below were
supplied by Meso Scale Discovery, Rockville, Md.): (1) block MSD
MULTI-SPOT.RTM. plate for 1 hour with appropriate MSD.RTM. blocking
solution and wash; (2) add 25 .mu.l assay diluent to each well, if
specified; (3) add 25 .mu.l calibrator, or sample (diluted as
appropriate) to each well; (4) incubate with shaking for 1-3 hours
(time as specified) and wash the well; (5) add 25 .mu.l labeled
detection antibody solution to each well; (6) incubate with shaking
for 1-2 hours (time as specified) and wash the well; (7) add 150
.mu.l MSD read buffer to each well; (8) read plate immediately on
MSD SECTOR.RTM. 6000 Reader.
[0093] The following biomarkers were elevated in serum samples of
GN patients relative to normal patients, Clusterin, KIM-1, aGST,
IL-6, CHGA, E-Cadherin, Timp-1, TNF-RI and TNF-RII (Table 4). Lower
serum levels of UMOD were also observed, a protein produced in the
kidney (Henle's loop) and excreted in the urine, indicating kidney
damage (Table 4, FIG. 1).
TABLE-US-00004 TABLE 4 Serum biomarkers with altered levels in GN
relative to patients with normal kidney function (N). Median values
are in pg/ml in serum. Biomarker Clusterin KIM-1 aGST UMOD IL-6
CHGA E-Cadherin Timp-l TNF-RI TNF-RII median GN 57,324,966 587
3,369 49,081 1.62 24,972 68,119 816,391 4,740 7,901 median N
25,705,457 211 1,640 122,308 0.41 7,306 26,247 258,562 2,004 2,966
medGN/medN 2.23 2.78 2.05 0.40 3.99 3.42 2.60 3.16 2.37 2.66
[0094] In urine samples, a larger number of proteins with altered
levels were identified, following normalization of these values to
urine creatinine to correct for urine volume. The following
biomarkers had elevated median values in GN patients: OPGN,
Calbindin, Clusterin, Osteoactin, Albumin, B2M, Cystatin C, NGAL,
MCP-1, IL-6, IL-15, CHGA, E-Cadherin, ICAM-1, KDR, LBP, PRDX4,
Prolactin, PSAT1, S100A4, TIMP-1, TNF-RI, TNF-RII and VCAM-1 (Table
5, FIG. 1). The following biomarkers had lower levels, EGF, UMOD,
SERPINB3 and ANXA1 (Table 5, FIG. 2).
TABLE-US-00005 TABLE 5 Urine biomarkers with altered levels in GN
relative to patients with normal kidney function (N). Median
normalized values were determined using the urine biomarker levels
normalized to urine creatinine (normalized biomarker value = [pg/ml
of biomarker]/[urine creatinine, mg/dl]. Biomarker OPGN Calbindin
Clusterin Osteoactin Albumin B2M Cystatin C EGF NGAL S100A4 median
GN 0.86 87 996 18.57 3,758,615 14,241 917 50 849 8.25 median N 0.23
31 158 6.74 35,912 697 296 102 312 1.85 medGN/medN 3.67 2.78 6.29
2.76 105 20.42 3.10 0.49 2.72 4.46 Biomarker ANXA1 CHGA E-Cadherin
ICAM-1 KDR LBP PRDX4 Prolactin PSAT1 median GN 1.59 0.90 119.24
48.88 1.98 10.02 23.16 1.08 0.35 median N 4.08 0.14 31.04 20.21
0.15 1.24 8.38 0.05 0.05 medGN/medN 0.39 6.53 3.84 2.42 13.51 8.06
2.76 23.48 7.20 Biomarker UMOD MCP-1 IL-6 IL-15 SERPINB3 TIMP-1
TNF-RI TNF-RII VCAM-1 median GN 70,843 3.03 0.022 0.017 2.69 13.88
46.64 91.68 26.70 median N 190,608 0.76 0.005 0.004 7.22 1.78 14.01
22.77 7.41 medGN/medN 0.37 3.98 4.56 4.42 0.37 7.79 3.33 4.03
3.61
[0095] As expected, the levels of albumin and other proteins were
significantly elevated in urine, indicating damage to the kidney,
allowing these proteins appear at elevated levels in the urine of
GN patients. Although a general elevation of protein levels might
have been expected across the biomarkers tested this did not prove
to be the case, indicating that additional disease-specific
diagnostic value was associated with these elevated biomarkers. In
the case of the biomarkers with lower levels in the GN patients,
these are of special interest since they contrast to the elevated
protein levels anticipated in patients with damaged kidneys, and as
such are especially valuable biomarkers for evaluating GN
disease.
[0096] In addition to the serum and urine biomarker levels, the
fractional excretion (FE) was calculated as a measure of the rate
of excretion of a biomarker
[FE=U/S[analyte]/U/S[creatinine].times.100%]. Using FE, the
following biomarkers were identified as having altered excretion
rates in GN patients, OPGN, Calbindin, Clusterin, Osteoactivin,
TFF3, B2M, Cystatin C, EGF, NGAL, MCP-1, IL-6, IL-8, IL-15, IL-7,
SERPINB3, CHGA, ICAM-1, KDR, LBP, PRDX4, Prolactin, PSAT1, S100A4,
TIMP-1, TNF-R1, TNF-RII and VCAM-1 (Table 6).
TABLE-US-00006 TABLE 6 Biomarkers with altered fractional excretion
(FE) rates, in GN relative to patients with normal kidney function
(N). Median normalized values were determined using the FE [FE =
U/S[analyte]/U/S[creatinine] .times. 100%]. Biomarker OPGN
Calbindin Clusterin Osteoactivin TFF3 B2M Cystatin C EGF NGAL
median GN 87% 124% 0.42% 10.90% 25.77% 42.53% 40.16% 2892% 38%
median N 12% 42% 0.05% 1.90% 9.53% 2.87% 2.34% 11812% 12%
medGN/medN 7.26 2.94 9.07 5.73 2.70 14.83 17.16 0.24 3.06 Biomarker
MCP-1 IL-6 IL-8 IL-15 IL-7 SERPINB3 CHGA ICAM-1 KDR median GN 102%
372% 174% 199% 32% 55% 0.83% 4.58% 1.32% median N 23% 68% 69% 23%
14% 223% 0.19% 1.15% 0.07% medGN/medN 4.43 5.50 2.53 8.71 2.21 0.25
4.28 4.00 17.82 Biomarker LBP PRDX4 Prolactin PSAT1 S100A4 TIMP-1
TNF-R1 TNF-RII VCAM-1 median GN 0.36% 12.75% 7.35% 1.31% 4.60%
0.47% 323% 232% 1.00% median N 0.03% 4.37% 0.05% 0.38% 0.91% 0.06%
56% 70% 0.20% medGN/medN 13.4 2.9 143.6 3.41 5.06 7.38 5.77 3.32
5.00
[0097] Various publications and test methods are cited herein, the
disclosures of which are incorporated herein by reference in their
entireties, In cases where the present specification and a document
incorporated by reference and/or referred to herein include
conflicting disclosure, and/or inconsistent use of terminology,
and/or the incorporated/referenced documents use or define terms
differently than they are used or defined in the present
specification, the present specification shall control.
REFERENCES
[0098] 1. Appel G B. Glomerular disorders and nephrotic syndromes.
In: Goldman L, Ausiello D, eds. Cecil Medicine. 23rd ed.
Philadelphia, Pa: Saunders Elsevier; 2007:chap 122. [0099] 2.
Nachman P H, Jennette J C, Falk R J. Primary glomerular disease.
In: Brenner B M, ed. Brenner and Rector's The Kidney. 8th ed.
Philadelphia, Pa.: Saunders Elsevier; 2007:chap 30.
* * * * *
References